NLP-implementation-on-whastapp-chats-using-python
This notebook was built to analyze Whatsapp conversations using the steps below: Step 1: Detecting {Date} and {Time} tokens Step 2: Detecting the {Author} token Step 3: Extracting and Combining tokens Step 4: Parsing the entire file and handling Multi-Line Messages For further steps, we need to perform Exploratory data analysis (EDA) Step 5: Performing EDA for analyzing chat data Step 6: Overall statistics of WhatsApp chat including Total number of messages, media messages(Omitted) & Total number of URLs Step 7: Extracting basic statistics for each Author (user) Step 8: Word cloud of most used words in chat Step 9: Total number of messages sent by each user Step 10: Total messages sent on each day of the week Step 11: Most active author of the chat Step 12: Most active day in a week In next steps, Time series analysis will be performed on chat data Step 13: Time whenever the chat was highly active Step 14: Date on which the chat was highly active Step 15: Converting 12-hour formate to 24 hours will help us for better analysis Step 16: Most suitable hour of the day whenever there will be more chances of getting a response from user
